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The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

DOE OSTI2023

An asynchronous parallel high-throughput model calibration framework for crystal plasticity finite element constitutive models

Crystal plasticity finite element model (CPFEM) is a powerful numerical simulation in the integrated computational materials engineering toolboxes that relates microstructures to homogenized materials properties and establishes the structure–property linkages in computational materials science. However, to establish the predictive capability, one needs to calibrate the underlying constitutive model, verify the solution and validate the model prediction against experimental data. Bayesian optimization (BO) has stood out as a gradient-free efficient global optimization algorithm that is capable of calibrating constitutive models for CPFEM. Here in this paper, we apply a recently developed asynchronous parallel constrained BO algorithm to calibrate phenomenological constitutive models for stainless steel 304 L, Tantalum, and Cantor high-entropy alloy.

304L stainless steel↗

NASA NTRS1976

Creep resistance

High-temperature structural applications usually require creep resistance because some average stress is maintained for prolonged periods. Alloy and microstructural design guidelines for creep resistance are presented through established knowledge on creep behavior and its functional dependences on alloy microstructure. Important considerations related to creep resistance of alloys as well as those that are harmful to high-temperature properties are examined. Although most of the creep models do not predict observed creep behavior quantitatively, they are sophisticated enough to provide alloy or microstructural design guidelines. It is shown that creep-resistant microstructures are usually in conflict with microstructures that improve such other properties as stress rupture ductility. Greater understanding of the effects of environments on creep and stress rupture behavior of materials is necessary before one can optimally design alloys for applications in different environments.

Tien, J. K.↗

DOE OSTI2020

Modular Growth and Nucleation Formulations in Modular Plasticity Models

Recent investigations like the second and third Sandia Fracture Challenges have characterized and demonstrated the performance of a variety of failure techniques and models. These surveys have considered a wide breadth of models encapsulating both general failure criteria as well as those focusing on pore nucleation and growth. Extensive reviews exist on both topics. The former category generally consists of classic models like the Johnson-Cook or Wilkins criteria. These models were recently added to modular plasticity models in the Library of Advanced Materials for Engineering (LAME) as criteria for use with element death capabilities. The latter category was not treated in that effort. There exists a large class of failure models based on predicting the evolution of pores and failure associated with such microstructures. While the exact mechanisms and corresponding impact on the macroscale behavior remain an active area of research, a large suite of formulations have been proposed combining different features of both pore nucleation and subsequent growth. The most famous of these are based on the popular Gurson model of pore growth derived via micromechanical analysis assuming a plastically incompressible matrix. Numerous other models exist for both growth and nucleation and the Cocks-Ashby growth and Horstemeyer-Gokhale nucleation models have been used successfully in recent Sandia Fracture Challenges. This specific combination is colloquially referred to as the "BCJ-failure model as it has been frequently used with the Bammann-Chisea-Johnson plasticity model.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Text Mining for Process–Structure–Properties Relationships in Metals

With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery—although significant challenges remain. While LLMs offer promising few- and zero-shot learning capabilities, particularly valuable in the materials domain where expert annotations are scarce, general-purpose LLMs often fail to address key materials-specific queries without further adaptation. To bridge this gap, fine-tuning LLMs on human-labeled data is essential for effective structured knowledge extraction (Liu in The Importance of Human-Labeled Data in the Era of LLMs, 2023). Here, in this study, we introduce a novel annotation schema designed to extract generic process–structure–properties relationships from scientific literature. We demonstrate the utility of this approach using a dataset of 128 abstracts, with annotations drawn from two distinct domains: high-temperature materials (Domain I) and uncertainty quantification in simulating materials microstructure (Domain II). Initially, we developed a conditional random field (CRF) model based on MatBERT—a domain-specific BERT variant—and evaluated its performance on Domain I. Subsequently, we compared this model with a fine-tuned LLM (GPT-4o from OpenAI) under identical conditions. Our results indicate that fine-tuning LLMs can significantly improve entity extraction performance over the BERT-CRF baseline on Domain I. However, when additional examples from Domain II were incorporated, the performance of the BERT-CRF model became comparable to that of the GPT-4o model. These findings underscore the potential of our schema for structured knowledge extraction and highlight the complementary strengths of both modeling approaches.

Materials science↗

DOE OSTI2020

Fluid Dynamics Effects on Microstructure Prediction in Single-Laser Tracks for Additive Manufacturing of IN625

Single-track laser fusion were simulated using a heat-transfer-solidification-only (HTS) model and its extension with fluid dynamics (HTS_FD) model using a parallel open-source code, which included laminar fluid dynamics, flat-free surface of the molten alloy, heat transfer, phase-change, evaporation, and surface tension phenomena. The results illustrate that the fluid dynamics affects the solidification and ensuing microstructure. For the HTS_FD simulations, thermal gradient, G was found to exhibit a maximum at the extremity of the solidified pool ( i.e. , at the free surface), while for HTS simulations, G exhibited a maximum around the entire edge of the solidified pool. HTS_FD simulations predicted a wider range of cooling rates than the HTS simulations, exhibited an increased spread in the solidification speed, V variation within the melt-pool with respect to the HTS model results. Primary dendrite arm spacing (PDAS) were evaluated based on power law correlations and marginal stability theory models using the ( G , V ) from HTS and HTS_FD simulations to quantify the effect of the fluid dynamics on the microstructure. At low-laser powers and low-scan speeds, the PDAS obtained with the fluid dynamics model (HTS_FD) was larger by more than 30 pct with respect to the PDAS calculated with the simple HTS model. A new PDAS correlation, i.e. , \( \lambda_{1} \left[ {\mu {\text{m}}} \right] = 832\;G\left[ {\text{K/m}} \right]^{ - 0.5} V\left[ {\text{m/s}} \right]^{ - 0.25} \) , which uses the ( G , V ) results from the HTS_FD model was developed and validated against experimental results.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Carbon Support Microstructure Impact on High Current Density Transport Resistances in PEMFC Cathode

Cell voltages at high current densities (HCD) of an operating proton-exchange membrane fuel cell (PEMFC) cathode suffer from losses due to the local-O 2 and bulk-H + transport resistances in the catalyst layer. Particularly, the microstructure of high surface area carbon (HSC) support upon which both the platinum catalyst and ionomer are dispersed play a pivotal role in controlling the reactant transport to the active site in the catalyst layer. In this study, we perform a systematic analysis of the underlying microstructure of platinum-cobalt catalyst dispersed on various HSC supports in terms of their surface area and pore-size distribution. The carbon microstructure was found to strongly influence the PtCo nanoparticle dispersion, catalyst layer ionomer distribution and transport losses governing the performance at HCD. Catalyst layer electrochemical diagnostics carried out to quantify local-O 2 transport resistance and bulk-H + transport resistance in the cathode were found to be directly correlated to the micropore (<2 nm) and macropore (>8 nm) surface areas of the carbon support, respectively. Finally, a 1D-performance model has been developed to assimilate our understanding of the catalyst layer microstructure and transport resistances at HCD.

25 ENERGY STORAGE↗

DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗

NASA NTRS1999

The Effects of Gravity on Combustion and Structure Formation During Synthesis of Advanced Materials

Combustion in a variety of heterogeneous systems, leading to the synthesis of advanced materials, is characterized by high temperatures (2000-3500 K) and heating rates (up to 10(exp 6) K/s) at and ahead of the reaction front. These high temperatures generate liquids and gases which are subject to gravity-driven flow. The removal of such gravitational effects is likely to provide increased control of the reaction front, with a consequent improvement in control of the microstructure of the synthesized products. Thus, microgravity experiments can lead to major advances in the understanding of fundamental aspects of combustion and structure formation under the extreme conditions of the combustion synthesis wave. In addition, the specific features of microgravity environment allow one to produce unique materials, which cannot be obtained under terrestrial conditions. The general goals of the current research are: 1) to improve the understanding of fundamental phenomena taking place during combustion of heterogeneous systems, 2) to use low-gravity experiments for insight into the physics and chemistry of materials synthesis processes, and 3) based on the obtained knowledge, to optimize processing conditions for synthesis of advanced materials with desired microstructures and properties. This research follows logically from the results of investigations we have conducted in the framework of our previous grant on gravity influence on combustion synthesis (CS) of gasless systems. Prior work, by others and by us, has clearly demonstrated that gravity plays an important role during combustion synthesis of materials. The immediate tasks for the future are to quantitatively identify the nature of observed effects, and to create accurate local kinetic models of the processes, which can lead to a control of the microstructure and properties of the synthesized materials. In summary, this is the value of the proposed research. Based on our prior work, we focus on the fundamental aspects of combustion and structure formation under the unique condition of microgravity.

Varma, A.↗

NASA NTRS1989

The high temperature deformation in cyclic loading of a single crystal nickel-base superalloy

The high temperature cyclic stress softening response of the single crystal nickel-base superalloy PWA 1480 was investigated. Specimens oriented near the 001- and 111-lines were tested at 1050 C in low-cycle fatigue and then microstructurally evaluated. The 001- and 111-line specimens had dissimilar flow behavior in monotonic tensile tests, but comparable softening in low-cycle fatigue. This softening was accompanied by rapid generation of dislocation networks at the gamma-gamma-prime interfaces and by a slower time-dependent coarsening of gamma-prime precipitates. Due to the rapid formation of a dislocation substructure at the gamma-gamma-prime interfaces, the cyclic stress softening could be modeled with an existing theory which related cyclic stress to the evolving microstructure and dislocation structure.

Gabb, T. P.↗

DOE OSTI2019

Microstructure Anisotropy Effects on Fracture and Fatigue Mechanisms in Shape Memory Alloy Martensites

The chief scientific object was to investigate the fatigue and fracture mechanisms in NiTi shape memory alloys, in the presence of stress concentrating factors such as micro-pores and notches. In particular, the interactions between structure (factors related to the geometry of the specimen, such as holes, pores and notches) and microstructure (related to properties of the material such as grains, secondary phases, twins) in influencing the inelastic deformation, leading up to fracture in NiTi was examined. Primarily, there were two major thrusts. The first thrust focused on fracture behavior in Shape Memory Alloys where the high crystal symmetry cubic phase transformed into the low symmetry phase during deformation and propagation of cracks. This thrust revealed the interplay between size of micro-pores, size of grains and grain orientations in determining the resistance to crack growth, during cyclic tensile deformation of porous-like NiTi specimens. The role of secondary phases (impurities of Ti, often formed during fabrication) were also shown to induce local inelastic deformation gradients during tensile deformation and reduce overall extent of deformation. The second thrust focused on the fatigue and fracture behavior in the low crystal symmetry martensite phase. Unlike high symmetry phases, characterization of deformation in low symmetry phases such as martensitic NiTi has been challenging, due to a hierarchical microstructure spanning from nanoscale twins to the macroscale, a highly anisotropic microstructure stemming from the low crystal symmetry and a multitude of inelastic mechanisms for deformation. Thus, advanced X-ray techniques such as 3D high-energy diffraction microscopy and x-ray micro-Laue diffraction and spectroscopy were used in conjunction with traditional techniques such as SEM and TEM to understand the inelastic deformation in the martensite phase in NiTi, in the presence of notches. This thrust revealed a stark difference in deformation mechanisms based on the nature of stress: regions near the notch experience a highly triaxial stress while those far away experience a uniaxial stress. Additionally, while regions close to the notch were shown to deform locally by amorphization/nanocrystallization, ultimately leading to fracture, regions far away from the notch deformed in a more traditional manner, with detwinning and twin reorientation the primary mechanisms of deformation. More importantly, this thrust revealed that in the presence of structural factors such as notches, the traditional picture of reorientation (coalescence) of nanoscale martensite twins into increasingly larger domains with increased loading does not hold true, even up to fracture of the specimen. These conclusions will inform the modeling and understanding of deformation behavior of specimens, where structure and microstructure coexist and interact.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Observational and numerical studies of extreme frontal scale contraction

The general objective of this effort is to increase understanding of how frontal scale contraction processes may create and sustain intense mesoscale precipitation along intensifying cold fronts. The five-part project (an expansion of the originally proposed two-part project) employed conventional meteorological data, special mesoscale data, remote sensing measurements, and various numerical models. First an idealized hydrostatic modeling study of the scale contraction effects of differential cloud cover on low-level frontal structure and dynamics was completed and published in a peer-reviewed journal. The second objective was to complete and publish the results from a three dimensional numerical model simulation of a cold front in which differential sensible heating related to cloud coverage patterns was apparently crucial in the formation of a severe frontal squall line. The third objective was to use a nonhydrostatic model to examine the nonlinear interactions between the transverse circulation arising from inhomogeneous cloud cover, the adiabatic frontal circulation related to semi-geostrophic forcing, and diabatic effects related to precipitation processes, in the development of a density current-like microstructure at the leading edge of cold fronts. Although the development of a frontal model that could be used to initialize such a primitive equation model was begun, we decided to focus our efforts instead on a project that could be successfully completed in this short time, due to the lack of prospects for continued NASA funding beyond this first year (our proposal was not accepted for future funding). Thus, a fourth task was added, which was to use the nonhydrostatic model to test tentative hypotheses developed from the most detailed observations ever obtained on a density current (primarily sodar and wind profiler data). These simulations were successfully completed, the findings were reported at a scientific conference, and the results have recently been submitted to a peer-reviewed journal. The fifth objective was to complete the analysis of data collected during the Cooperative Oklahoma Profiler Studies (COPS-91) field project, which was supported by NASA. The analysis of the mesoscale surface and sounding data, Doppler radar imagery, and other remote sensing data from multi frequency wind profiler, microwave radiometer, and the Radio Acoustic Sounding System has been completed. This study is a unique investigation of processes that caused the contraction of a cold front to a microscale zone exhibiting an undular bore-like structure. Results were reported at a scientific conference and are being prepared for publication. In summary, considerable progress has been achieved under NASA funding in furthering our understanding of frontal scale contraction and density current - gravity wave interaction processes, and in utilizing models and remotely sensed data in such studies.

Koch, Steven E.↗

DOE OSTI2022

Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components

Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Identification of mechanisms driving heterogeneous void growth in ductile aluminum

Void growth plays a central role in ductile fracture, yet the specific mechanisms that control this remain obscure. Classical models, such as those proposed by Rice and Tracey in 1969, are able to capture average rates of void growth, but cannot capture the heterogeneity of individual void growth. Building on recent work, the present study employs laboratory-based diffraction contrast tomography and in-situ x-ray computed tomography to investigate the effect of grain structure and other microstructural factors on void growth in an Al-2219 alloy. Crystal plasticity finite element (CP-FE) modeling is used alongside experimental data to evaluate the contributions of local mechanical states, grain orientation, grain size, and neighboring microstructural features. No strong linear relationships are found with any of the considered descriptors and void growth rate. Potential complex nonlinear relationships are explored with the use of a random forest regression model, which identifies initial void volume, void aspect ratio, local normal stress state, local shear stress state, and local equivalent plastic strain (EQPS) as features that most improve void growth rate predictions. The combination of these analyses suggests that these features should be prioritized to improve models of void growth.

Diffraction contrast tomography (DCT)↗

DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

NASA NTRS2012

Modeling of Damage Initiation and Progression in a SiC/SiC Woven Ceramic Matrix Composite

The goal of an ongoing project at NASA Glenn is to investigate the effects of the complex microstructure of a woven ceramic matrix composite and its variability on the effective properties and the durability of the material. Detailed analysis of these complex microstructures may provide clues for the material scientists who `design the material? or to structural analysts and designers who `design with the material? regarding damage initiation and damage propagation. A model material system, specifically a five-harness satin weave architecture CVI SiC/SiC composite composed of Sylramic-iBN fibers and a SiC matrix, has been analyzed. Specimens of the material were serially sectioned and polished to capture the detailed images of fiber tows, matrix and porosity. Open source analysis tools were used to isolate various constituents and finite elements models were then generated from simplified models of those images. Detailed finite element analyses were performed that examine how the variability in the local microstructure affected the macroscopic behavior as well as the local damage initiation and progression. Results indicate that the locations where damage initiated and propagated is linked to specific microstructural features.

Mital, Subodh K.↗

DOE OSTI2021

Development of High-Performance Ni-base Alloys for Gas Turbine Wheels Using a Coprecipitation Approach (Final Technical Report)

In this project, a synergistic approach involving experiments informed by modelling was used to develop γ'/γ'' coprecipitation-strengthened Ni-base superalloys for land-based gas turbine wheels. In thick sections of such turbine wheels, the slow cooling rate normally observed, as well as variations in cooling rate could potentially result in drastically inhomogeneous and coarsened microstructure. Thus, ten alloy compositions were selected based on coprecipitation and sluggish γ’ growth and coarsening during three iterations of alloy development, assisted by extensive CALPHAD modeling. Phase equilibrium calculations, informed by the characterization of early alloys, were successful in predicting suitable aging treatments to obtain bimodal coprecipitate distribution in several alloys. These aging treatments were applied to the subsequent round of alloys and the resulting microstructures were characterized in detail. Two different cooling rates were used during each of these heat treatments to simulate the range of cooling rates observed in a thick section forging. The microstructures were used to calibrate a multi-phase field model (MPF), which was used to study the formation mechanisms of various coprecipitate morphologies observed in the experiments. Following this, the most promising alloys in each round were selected and studied using high temperature tensile and creep tests. Considering that a slower cooling rate would lead to a strength debit, while a faster cooling rate might lead to a decline in creep rupture life of a full-scale wheel, tensile tests were carried out for slower cooled samples, while creep tests were carried out for faster cooled samples. The deformation microstructures were then characterized using advanced characterization techniques such as Diffraction Contrast-Scanning Transmission Electron Microscopy (DC-STEM) and Electron Channeling Contrast Imaging (ECCI). Further, a mean-field creep model was developed and calibrated using these experimental findings to predict long-term creep behavior of these coprecipitation-strengthened alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Elucidating the Morphological Instability Mechanisms During Electrodeposition of Active Metals

The primary aim of this investigation is to elucidate the mechanisms by which a group of metals pertinent to battery technology exhibit unstable growth morphology during electrodeposition, which are crucial for the operational efficacy of batteries. The metals under consideration include alkali metals alongside zinc, all of which are characterized by high atomic mobility and reactivity with the electrolytes employed in battery systems. These materials represent promising electrode candidates for next-generation rechargeable batteries that are anticipated to deliver significantly enhanced energy density at a reduced cost. Nevertheless, the widespread occurrence of distinctly non-uniform morphologies, exemplified by the emergence of filamentous and moss-like structures, constitutes a significant impediment to their effective utilization, as it leads to accelerated capacity degradation and potential internal short circuits. This study addresses a critical question that has thus far garnered limited attention: Does the residual stress induced by the plating process play an instrumental role in inducing the morphological instability? Utilizing zinc as the primary model system, this project will be executed through three interconnected tasks: (1) the quantification of the relationship between plating stress and electroplating morphologies, (2) the three-dimensional imaging of the microstructure of the mossy structure at the nanoscale, and (3) the development of a mesoscale electroplating model to interpret empirical findings and generate additional predictive insights.

25 ENERGY STORAGE↗